""" 智能食物数据库和热量估算模块 简化用户数据录入过程 """ from typing import Dict, List, Optional, Tuple import json from pathlib import Path class SmartFoodDatabase: """智能食物数据库""" def __init__(self): self.food_database = self._load_food_database() self.portion_sizes = self._load_portion_sizes() self.calorie_estimates = self._load_calorie_estimates() # 添加缓存 self.ai_cache = {} # AI分析结果缓存 self.calorie_cache = {} # 热量估算缓存 self.search_cache = {} # 搜索结果缓存 # 预计算常用食物 self._precompute_common_foods() def _load_food_database(self) -> Dict[str, Dict]: """加载食物数据库""" return { # 主食类 "米饭": {"category": "主食", "calories_per_100g": 130, "protein": 2.7, "carbs": 28, "fat": 0.3}, "面条": {"category": "主食", "calories_per_100g": 131, "protein": 5, "carbs": 25, "fat": 1.1}, "馒头": {"category": "主食", "calories_per_100g": 221, "protein": 7, "carbs": 47, "fat": 1.1}, "包子": {"category": "主食", "calories_per_100g": 227, "protein": 7.3, "carbs": 45, "fat": 2.6}, "饺子": {"category": "主食", "calories_per_100g": 250, "protein": 11, "carbs": 35, "fat": 8}, "粥": {"category": "主食", "calories_per_100g": 50, "protein": 1.1, "carbs": 10, "fat": 0.3}, "燕麦": {"category": "主食", "calories_per_100g": 389, "protein": 17, "carbs": 66, "fat": 7}, "面包": {"category": "主食", "calories_per_100g": 265, "protein": 9, "carbs": 49, "fat": 3.2}, "饼干": {"category": "主食", "calories_per_100g": 433, "protein": 9, "carbs": 71, "fat": 12}, "薯条": {"category": "主食", "calories_per_100g": 319, "protein": 4, "carbs": 41, "fat": 15}, "玉米": {"category": "主食", "calories_per_100g": 86, "protein": 3.4, "carbs": 19, "fat": 1.2}, "红薯": {"category": "主食", "calories_per_100g": 86, "protein": 1.6, "carbs": 20, "fat": 0.1}, # 蛋白质类 "鸡蛋": {"category": "蛋白质", "calories_per_100g": 155, "protein": 13, "carbs": 1.1, "fat": 11}, "鸡肉": {"category": "蛋白质", "calories_per_100g": 165, "protein": 31, "carbs": 0, "fat": 3.6}, "猪肉": {"category": "蛋白质", "calories_per_100g": 143, "protein": 20, "carbs": 0, "fat": 6.2}, "牛肉": {"category": "蛋白质", "calories_per_100g": 250, "protein": 26, "carbs": 0, "fat": 15}, "鱼肉": {"category": "蛋白质", "calories_per_100g": 206, "protein": 22, "carbs": 0, "fat": 12}, "豆腐": {"category": "蛋白质", "calories_per_100g": 76, "protein": 8, "carbs": 2, "fat": 4.8}, "牛奶": {"category": "蛋白质", "calories_per_100g": 42, "protein": 3.4, "carbs": 5, "fat": 1}, "酸奶": {"category": "蛋白质", "calories_per_100g": 59, "protein": 3.3, "carbs": 4.7, "fat": 3.2}, "虾": {"category": "蛋白质", "calories_per_100g": 99, "protein": 24, "carbs": 0, "fat": 0.2}, "蟹": {"category": "蛋白质", "calories_per_100g": 97, "protein": 20, "carbs": 0, "fat": 1.5}, "鸭肉": {"category": "蛋白质", "calories_per_100g": 183, "protein": 25, "carbs": 0, "fat": 9}, "羊肉": {"category": "蛋白质", "calories_per_100g": 203, "protein": 25, "carbs": 0, "fat": 11}, "火腿": {"category": "蛋白质", "calories_per_100g": 145, "protein": 18, "carbs": 1.5, "fat": 7.5}, "香肠": {"category": "蛋白质", "calories_per_100g": 301, "protein": 13, "carbs": 2, "fat": 25}, # 蔬菜类 "白菜": {"category": "蔬菜", "calories_per_100g": 17, "protein": 1.5, "carbs": 3.2, "fat": 0.1}, "菠菜": {"category": "蔬菜", "calories_per_100g": 23, "protein": 2.9, "carbs": 3.6, "fat": 0.4}, "西兰花": {"category": "蔬菜", "calories_per_100g": 34, "protein": 2.8, "carbs": 7, "fat": 0.4}, "胡萝卜": {"category": "蔬菜", "calories_per_100g": 41, "protein": 0.9, "carbs": 10, "fat": 0.2}, "土豆": {"category": "蔬菜", "calories_per_100g": 77, "protein": 2, "carbs": 17, "fat": 0.1}, "西红柿": {"category": "蔬菜", "calories_per_100g": 18, "protein": 0.9, "carbs": 3.9, "fat": 0.2}, "黄瓜": {"category": "蔬菜", "calories_per_100g": 16, "protein": 0.7, "carbs": 4, "fat": 0.1}, "茄子": {"category": "蔬菜", "calories_per_100g": 25, "protein": 1.1, "carbs": 6, "fat": 0.2}, "豆角": {"category": "蔬菜", "calories_per_100g": 31, "protein": 2.1, "carbs": 7, "fat": 0.2}, "韭菜": {"category": "蔬菜", "calories_per_100g": 25, "protein": 2.4, "carbs": 4, "fat": 0.4}, "芹菜": {"category": "蔬菜", "calories_per_100g": 16, "protein": 0.7, "carbs": 4, "fat": 0.1}, "洋葱": {"category": "蔬菜", "calories_per_100g": 40, "protein": 1.1, "carbs": 9, "fat": 0.1}, "大蒜": {"category": "蔬菜", "calories_per_100g": 149, "protein": 6.4, "carbs": 33, "fat": 0.5}, "生姜": {"category": "蔬菜", "calories_per_100g": 80, "protein": 1.8, "carbs": 18, "fat": 0.8}, # 水果类 "苹果": {"category": "水果", "calories_per_100g": 52, "protein": 0.3, "carbs": 14, "fat": 0.2}, "香蕉": {"category": "水果", "calories_per_100g": 89, "protein": 1.1, "carbs": 23, "fat": 0.3}, "橙子": {"category": "水果", "calories_per_100g": 47, "protein": 0.9, "carbs": 12, "fat": 0.1}, "葡萄": {"category": "水果", "calories_per_100g": 44, "protein": 0.2, "carbs": 11, "fat": 0.2}, "草莓": {"category": "水果", "calories_per_100g": 32, "protein": 0.7, "carbs": 8, "fat": 0.3}, "西瓜": {"category": "水果", "calories_per_100g": 30, "protein": 0.6, "carbs": 8, "fat": 0.1}, "梨": {"category": "水果", "calories_per_100g": 57, "protein": 0.4, "carbs": 15, "fat": 0.1}, "桃子": {"category": "水果", "calories_per_100g": 39, "protein": 0.9, "carbs": 10, "fat": 0.3}, "樱桃": {"category": "水果", "calories_per_100g": 63, "protein": 1.1, "carbs": 16, "fat": 0.2}, "柠檬": {"category": "水果", "calories_per_100g": 29, "protein": 1.1, "carbs": 9, "fat": 0.3}, "芒果": {"category": "水果", "calories_per_100g": 60, "protein": 0.8, "carbs": 15, "fat": 0.4}, "菠萝": {"category": "水果", "calories_per_100g": 50, "protein": 0.5, "carbs": 13, "fat": 0.1}, "猕猴桃": {"category": "水果", "calories_per_100g": 61, "protein": 1.1, "carbs": 15, "fat": 0.5}, # 坚果类 "花生": {"category": "坚果", "calories_per_100g": 567, "protein": 25, "carbs": 16, "fat": 49}, "核桃": {"category": "坚果", "calories_per_100g": 654, "protein": 15, "carbs": 14, "fat": 65}, "杏仁": {"category": "坚果", "calories_per_100g": 579, "protein": 21, "carbs": 22, "fat": 50}, "腰果": {"category": "坚果", "calories_per_100g": 553, "protein": 18, "carbs": 30, "fat": 44}, "开心果": {"category": "坚果", "calories_per_100g": 560, "protein": 20, "carbs": 28, "fat": 45}, "瓜子": {"category": "坚果", "calories_per_100g": 606, "protein": 19, "carbs": 20, "fat": 53}, # 饮料类 "水": {"category": "饮料", "calories_per_100g": 0, "protein": 0, "carbs": 0, "fat": 0}, "茶": {"category": "饮料", "calories_per_100g": 1, "protein": 0.1, "carbs": 0.3, "fat": 0}, "咖啡": {"category": "饮料", "calories_per_100g": 2, "protein": 0.1, "carbs": 0.3, "fat": 0}, "果汁": {"category": "饮料", "calories_per_100g": 45, "protein": 0.3, "carbs": 11, "fat": 0.1}, "可乐": {"category": "饮料", "calories_per_100g": 42, "protein": 0, "carbs": 10.6, "fat": 0}, "雪碧": {"category": "饮料", "calories_per_100g": 40, "protein": 0, "carbs": 10, "fat": 0}, "啤酒": {"category": "饮料", "calories_per_100g": 43, "protein": 0.5, "carbs": 3.6, "fat": 0}, "红酒": {"category": "饮料", "calories_per_100g": 83, "protein": 0.1, "carbs": 2.6, "fat": 0}, "白酒": {"category": "饮料", "calories_per_100g": 298, "protein": 0, "carbs": 0, "fat": 0}, # 调料类 "盐": {"category": "调料", "calories_per_100g": 0, "protein": 0, "carbs": 0, "fat": 0}, "糖": {"category": "调料", "calories_per_100g": 387, "protein": 0, "carbs": 100, "fat": 0}, "酱油": {"category": "调料", "calories_per_100g": 63, "protein": 7, "carbs": 7, "fat": 0}, "醋": {"category": "调料", "calories_per_100g": 31, "protein": 0.1, "carbs": 7, "fat": 0}, "油": {"category": "调料", "calories_per_100g": 884, "protein": 0, "carbs": 0, "fat": 100}, "辣椒": {"category": "调料", "calories_per_100g": 40, "protein": 1.9, "carbs": 9, "fat": 0.4}, "胡椒": {"category": "调料", "calories_per_100g": 251, "protein": 10, "carbs": 64, "fat": 3.3}, "花椒": {"category": "调料", "calories_per_100g": 258, "protein": 6, "carbs": 37, "fat": 8.9}, } def _load_portion_sizes(self) -> Dict[str, List[str]]: """加载分量选项""" return { "主食": ["1小碗", "1中碗", "1大碗", "1个", "2个", "3个", "半份", "1份", "2份"], "蛋白质": ["1个", "2个", "3个", "1小块", "2小块", "1片", "2片", "1杯", "2杯", "适量"], "蔬菜": ["1小份", "1中份", "1大份", "1把", "2把", "1根", "2根", "适量", "很多"], "水果": ["1个", "2个", "3个", "1小个", "1大个", "1片", "2片", "适量"], "坚果": ["1小把", "1把", "2把", "1颗", "2颗", "3颗", "适量"], "饮料": ["1杯", "2杯", "3杯", "1小杯", "1大杯", "1瓶", "2瓶", "适量"], "调料": ["1小勺", "1勺", "2勺", "1小匙", "1匙", "2匙", "适量", "少许"] } def _load_calorie_estimates(self) -> Dict[str, Dict]: """加载热量估算""" return { "1小碗": {"米饭": 130, "面条": 131, "粥": 50}, "1中碗": {"米饭": 195, "面条": 196, "粥": 75}, "1大碗": {"米饭": 260, "面条": 262, "粥": 100}, "1个": {"鸡蛋": 77, "苹果": 52, "香蕉": 89, "馒头": 221, "包子": 227}, "2个": {"鸡蛋": 154, "苹果": 104, "香蕉": 178, "馒头": 442, "包子": 454}, "1小块": {"鸡肉": 50, "猪肉": 50, "牛肉": 50, "豆腐": 50}, "2小块": {"鸡肉": 100, "猪肉": 100, "牛肉": 100, "豆腐": 100}, "1杯": {"牛奶": 150, "酸奶": 150, "水": 0, "茶": 0, "咖啡": 0}, "2杯": {"牛奶": 300, "酸奶": 300, "水": 0, "茶": 0, "咖啡": 0}, "1小份": {"白菜": 50, "菠菜": 50, "西兰花": 50, "胡萝卜": 50}, "1中份": {"白菜": 100, "菠菜": 100, "西兰花": 100, "胡萝卜": 100}, "1大份": {"白菜": 150, "菠菜": 150, "西兰花": 150, "胡萝卜": 150}, "1小把": {"花生": 30, "核桃": 30, "杏仁": 30}, "1把": {"花生": 60, "核桃": 60, "杏仁": 60}, "适量": {"default": 50}, # 默认适量为50卡路里 "很多": {"default": 150}, # 默认很多为150卡路里 "1小勺": {"盐": 0, "糖": 16, "酱油": 3, "醋": 2, "油": 44, "辣椒": 2, "胡椒": 13, "花椒": 13}, "1勺": {"盐": 0, "糖": 32, "酱油": 6, "醋": 4, "油": 88, "辣椒": 4, "胡椒": 25, "花椒": 26}, "2勺": {"盐": 0, "糖": 64, "酱油": 12, "醋": 8, "油": 176, "辣椒": 8, "胡椒": 50, "花椒": 52}, "1小匙": {"盐": 0, "糖": 8, "酱油": 1.5, "醋": 1, "油": 22, "辣椒": 1, "胡椒": 6, "花椒": 6}, "1匙": {"盐": 0, "糖": 16, "酱油": 3, "醋": 2, "油": 44, "辣椒": 2, "胡椒": 13, "花椒": 13}, "2匙": {"盐": 0, "糖": 32, "酱油": 6, "醋": 4, "油": 88, "辣椒": 4, "胡椒": 25, "花椒": 26}, "少许": {"default": 5}, # 默认少许为5卡路里 } def search_foods(self, query: str) -> List[Dict]: """搜索食物（优化版本）""" query = query.lower().strip() # 检查缓存 if query in self.search_cache: return self.search_cache[query] results = [] # 精确匹配优先 for food_name, food_info in self.food_database.items(): if query == food_name.lower(): results.insert(0, { "name": food_name, "category": food_info["category"], "calories_per_100g": food_info["calories_per_100g"], "match_type": "exact" }) # 包含匹配 for food_name, food_info in self.food_database.items(): if query in food_name.lower() and query != food_name.lower(): results.append({ "name": food_name, "category": food_info["category"], "calories_per_100g": food_info["calories_per_100g"], "match_type": "contains" }) # 关键词匹配 if len(results) < 5: keywords = query.split() for food_name, food_info in self.food_database.items(): if any(keyword in food_name.lower() for keyword in keywords): if not any(r["name"] == food_name for r in results): results.append({ "name": food_name, "category": food_info["category"], "calories_per_100g": food_info["calories_per_100g"], "match_type": "keyword" }) # 限制结果数量并缓存 results = results[:10] self.search_cache[query] = results return results def get_food_info(self, food_name: str) -> Optional[Dict]: """获取食物信息""" return self.food_database.get(food_name) def get_portion_options(self, food_name: str) -> List[str]: """获取分量选项""" food_info = self.get_food_info(food_name) if not food_info: return ["适量"] category = food_info["category"] return self.portion_sizes.get(category, ["适量"]) def estimate_calories(self, food_name: str, portion: str) -> int: """估算热量（优化版本）""" # 检查缓存 cache_key = f"{food_name}_{portion}" if cache_key in self.calorie_cache: return self.calorie_cache[cache_key] # 首先尝试精确匹配 if portion in self.calorie_estimates: portion_data = self.calorie_estimates[portion] if food_name in portion_data: calories = portion_data[food_name] self.calorie_cache[cache_key] = calories return calories elif "default" in portion_data: calories = portion_data["default"] self.calorie_cache[cache_key] = calories return calories # 使用快速估算 calories = self._calculate_calories_fast(food_name, portion) self.calorie_cache[cache_key] = calories return calories def _estimate_weight(self, portion: str, category: str) -> int: """估算重量（克）""" weight_estimates = { "1小碗": 100, "1中碗": 150, "1大碗": 200, "1个": 50, "2个": 100, "3个": 150, "1小块": 30, "2小块": 60, "1片": 20, "2片": 40, "1杯": 150, "2杯": 300, "1小份": 50, "1中份": 100, "1大份": 150, "1把": 30, "2把": 60, "1根": 100, "2根": 200, "1小把": 15, "1把": 30, "2把": 60, "1颗": 10, "2颗": 20, "3颗": 30, "1小勺": 5, "1勺": 10, "2勺": 20, "1小匙": 3, "1匙": 5, "2匙": 10, "适量": 50, "很多": 150, "少许": 2 } return weight_estimates.get(portion, 50) def _precompute_common_foods(self): """预计算常用食物的热量""" common_foods = [ "米饭", "面条", "馒头", "包子", "饺子", "粥", "面包", "鸡蛋", "鸡肉", "猪肉", "牛肉", "鱼肉", "豆腐", "牛奶", "酸奶", "白菜", "菠菜", "西兰花", "胡萝卜", "土豆", "西红柿", "黄瓜", "苹果", "香蕉", "橙子", "葡萄", "草莓", "西瓜" ] common_portions = ["1小碗", "1中碗", "1大碗", "1个", "2个", "1小块", "2小块", "1杯", "2杯"] for food in common_foods: for portion in common_portions: cache_key = f"{food}_{portion}" if cache_key not in self.calorie_cache: calories = self._calculate_calories_fast(food, portion) self.calorie_cache[cache_key] = calories def _calculate_calories_fast(self, food_name: str, portion: str) -> int: """快速计算热量（不使用AI）""" # 首先尝试精确匹配 if portion in self.calorie_estimates: portion_data = self.calorie_estimates[portion] if food_name in portion_data: return portion_data[food_name] elif "default" in portion_data: return portion_data["default"] # 使用食物数据库估算 food_info = self.get_food_info(food_name) if food_info: weight_estimate = self._estimate_weight(portion, food_info["category"]) calories = int(food_info["calories_per_100g"] * weight_estimate / 100) return max(calories, 10) # 基于食物名称的快速估算 return self._quick_estimate_by_name(food_name, portion) def _quick_estimate_by_name(self, food_name: str, portion: str) -> int: """基于食物名称的快速估算""" # 食物类型快速估算 if any(keyword in food_name for keyword in ["米饭", "面条", "馒头", "包子", "饺子", "粥", "面包"]): base_calories = 200 # 主食基础热量 elif any(keyword in food_name for keyword in ["鸡蛋", "鸡肉", "猪肉", "牛肉", "鱼肉", "豆腐", "牛奶", "酸奶"]): base_calories = 150 # 蛋白质基础热量 elif any(keyword in food_name for keyword in ["白菜", "菠菜", "西兰花", "胡萝卜", "土豆", "西红柿", "黄瓜"]): base_calories = 50 # 蔬菜基础热量 elif any(keyword in food_name for keyword in ["苹果", "香蕉", "橙子", "葡萄", "草莓", "西瓜"]): base_calories = 80 # 水果基础热量 else: base_calories = 100 # 默认基础热量 # 根据分量调整 portion_multiplier = { "1小碗": 0.8, "1中碗": 1.0, "1大碗": 1.5, "1个": 0.6, "2个": 1.2, "3个": 1.8, "1小块": 0.4, "2小块": 0.8, "1杯": 1.0, "2杯": 2.0, "适量": 0.8, "很多": 1.5 } multiplier = portion_multiplier.get(portion, 1.0) return int(base_calories * multiplier) def _estimate_calories_with_ai(self, food_name: str, portion: str) -> int: """使用AI估算食物热量""" try: from llm_integration.qwen_client import get_qwen_client client = get_qwen_client() # 构建AI提示词 system_prompt = """ 你是一个专业的营养师，擅长估算食物的热量和营养成分。 你的任务是： 1. 根据食物名称和分量估算热量 2. 提供准确的营养信息 3. 考虑食物的常见制作方式 请以JSON格式返回结果，包含以下字段： - calories: 估算的热量值（整数） - category: 食物分类 - confidence: 置信度(0-1) - reasoning: 估算理由 注意： - 热量值应该是整数 - 考虑食物的常见分量 - 基于科学的营养学知识 - 如果不确定，给出保守估算 """ user_prompt = f""" 请估算以下食物的热量： 食物名称: {food_name} 分量: {portion} 请提供： 1. 估算的热量值（卡路里） 2. 食物分类 3. 估算理由 4. 置信度 请以JSON格式返回结果。 """ messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt} ] response = client.chat_completion(messages, temperature=0.2, max_tokens=500) if response and 'choices' in response: content = response['choices'][0]['message']['content'] result = self._parse_ai_calorie_result(content) if result.get('success'): calories = result.get('calories', 50) # 将AI估算的食物添加到缓存 self._cache_ai_food_info(food_name, result) return max(calories, 10) else: print(f"AI解析失败: {result}") return 50 except Exception as e: print(f"AI热量估算失败: {e}") # 如果AI估算失败，返回默认值 return 50 def _parse_ai_calorie_result(self, content: str) -> Dict: """解析AI热量估算结果""" try: import json # 尝试提取JSON部分 start_idx = content.find('{') end_idx = content.rfind('}') + 1 if start_idx != -1 and end_idx != -1: json_str = content[start_idx:end_idx] result_dict = json.loads(json_str) return { 'success': True, 'calories': int(result_dict.get('calories', 50)), 'category': result_dict.get('category', '其他'), 'confidence': float(result_dict.get('confidence', 0.5)), 'reasoning': result_dict.get('reasoning', 'AI估算') } except Exception as e: print(f"解析AI结果失败: {e}") return {'success': False, 'calories': 50} def _cache_ai_food_info(self, food_name: str, ai_result: Dict): """缓存AI估算的食物信息""" try: # 将AI估算的食物添加到内存数据库 self.food_database[food_name] = { "category": ai_result.get('category', '其他'), "calories_per_100g": ai_result.get('calories', 50), "protein": 0, # AI暂时不提供详细营养成分 "carbs": 0, "fat": 0, "ai_estimated": True, # 标记为AI估算 "confidence": ai_result.get('confidence', 0.5) } except Exception as e: print(f"缓存AI食物信息失败: {e}") def get_food_categories(self) -> List[str]: """获取食物分类""" return ["主食", "蛋白质", "蔬菜", "水果", "坚果", "饮料", "调料"] def get_foods_by_category(self, category: str) -> List[str]: """根据分类获取食物列表""" foods = [] for food_name, food_info in self.food_database.items(): if food_info["category"] == category: foods.append(food_name) return foods def analyze_food_with_ai(self, food_name: str, portion: str) -> Dict: """使用AI分析食物详细信息""" try: from llm_integration.qwen_client import get_qwen_client client = get_qwen_client() # 构建AI提示词 system_prompt = """ 你是一个专业的营养师和食物分析专家，擅长分析食物的营养成分和健康价值。 你的任务是： 1. 分析食物的详细营养成分 2. 估算热量和主要营养素含量 3. 提供健康建议 4. 考虑食物的制作方式 请以JSON格式返回结果，包含以下字段： - calories: 热量值（整数） - protein: 蛋白质含量（克） - carbs: 碳水化合物含量（克） - fat: 脂肪含量（克） - fiber: 纤维含量（克） - category: 食物分类 - health_tips: 健康建议列表 - cooking_suggestions: 制作建议列表 - confidence: 置信度(0-1) - reasoning: 分析理由 注意： - 所有数值应该是数字 - 基于科学的营养学知识 - 考虑食物的常见制作方式 - 提供实用的健康建议 """ user_prompt = f""" 请详细分析以下食物： 食物名称: {food_name} 分量: {portion} 请提供： 1. 详细的营养成分分析 2. 热量和主要营养素含量 3. 食物分类 4. 健康建议 5. 制作建议 6. 分析理由 请以JSON格式返回结果。 """ messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt} ] response = client.chat_completion(messages, temperature=0.2, max_tokens=800) if response and 'choices' in response: content = response['choices'][0]['message']['content'] result = self._parse_ai_food_analysis(content) if result.get('success'): # 缓存AI分析结果 self._cache_ai_food_analysis(food_name, result) return result else: print(f"AI食物分析解析失败: {result}") return self._get_fallback_food_analysis(food_name, portion) except Exception as e: print(f"AI食物分析失败: {e}") # 如果AI分析失败，返回基础估算 return self._get_fallback_food_analysis(food_name, portion) def _get_fallback_food_analysis(self, food_name: str, portion: str) -> Dict: """获取备用食物分析结果""" return { 'success': False, 'calories': self.estimate_calories(food_name, portion), 'protein': 0, 'carbs': 0, 'fat': 0, 'fiber': 0, 'category': '其他', 'health_tips': ['保持均衡饮食'], 'cooking_suggestions': ['简单烹饪'], 'confidence': 0.3, 'reasoning': '基础估算' } def _parse_ai_food_analysis(self, content: str) -> Dict: """解析AI食物分析结果""" try: import json # 尝试提取JSON部分 start_idx = content.find('{') end_idx = content.rfind('}') + 1 if start_idx != -1 and end_idx != -1: json_str = content[start_idx:end_idx] result_dict = json.loads(json_str) return { 'success': True, 'calories': int(result_dict.get('calories', 50)), 'protein': float(result_dict.get('protein', 0)), 'carbs': float(result_dict.get('carbs', 0)), 'fat': float(result_dict.get('fat', 0)), 'fiber': float(result_dict.get('fiber', 0)), 'category': result_dict.get('category', '其他'), 'health_tips': result_dict.get('health_tips', ['保持均衡饮食']), 'cooking_suggestions': result_dict.get('cooking_suggestions', ['简单烹饪']), 'confidence': float(result_dict.get('confidence', 0.5)), 'reasoning': result_dict.get('reasoning', 'AI分析') } except Exception as e: print(f"解析AI食物分析结果失败: {e}") return {'success': False} def _cache_ai_food_analysis(self, food_name: str, analysis_result: Dict): """缓存AI食物分析结果""" try: # 将AI分析的食物添加到内存数据库 self.food_database[food_name] = { "category": analysis_result.get('category', '其他'), "calories_per_100g": analysis_result.get('calories', 50), "protein": analysis_result.get('protein', 0), "carbs": analysis_result.get('carbs', 0), "fat": analysis_result.get('fat', 0), "fiber": analysis_result.get('fiber', 0), "ai_estimated": True, "confidence": analysis_result.get('confidence', 0.5), "health_tips": analysis_result.get('health_tips', []), "cooking_suggestions": analysis_result.get('cooking_suggestions', []) } except Exception as e: print(f"缓存AI食物分析结果失败: {e}") class SmartMealRecorder: """智能餐食记录器""" def __init__(self): self.food_db = SmartFoodDatabase() def record_meal_smart(self, user_id: str, meal_data: Dict) -> bool: """智能记录餐食""" try: # 自动估算热量 total_calories = 0 for food_item in meal_data.get("foods", []): food_name = food_item.get("name", "") portion = food_item.get("portion", "适量") calories = self.food_db.estimate_calories(food_name, portion) total_calories += calories food_item["estimated_calories"] = calories # 更新总热量 meal_data["total_calories"] = total_calories # 保存到数据库 from modules.data_collection import record_meal return record_meal(user_id, meal_data) except Exception as e: print(f"智能记录餐食失败: {e}") return False def suggest_foods(self, category: str = None) -> List[str]: """建议食物""" if category: return self.food_db.get_foods_by_category(category) else: # 返回所有食物 return list(self.food_db.food_database.keys()) def search_foods(self, query: str) -> List[Dict]: """搜索食物""" return self.food_db.search_foods(query) # 全局实例 smart_meal_recorder = SmartMealRecorder() # 便捷函数 def search_foods(query: str) -> List[Dict]: """搜索食物""" return smart_meal_recorder.search_foods(query) def get_food_categories() -> List[str]: """获取食物分类""" return smart_meal_recorder.food_db.get_food_categories() def get_foods_by_category(category: str) -> List[str]: """根据分类获取食物""" return smart_meal_recorder.food_db.get_foods_by_category(category) def get_portion_options(food_name: str) -> List[str]: """获取分量选项""" return smart_meal_recorder.food_db.get_portion_options(food_name) def estimate_calories(food_name: str, portion: str) -> int: """估算热量""" return smart_meal_recorder.food_db.estimate_calories(food_name, portion) def record_meal_smart(user_id: str, meal_data: Dict) -> bool: """智能记录餐食""" return smart_meal_recorder.record_meal_smart(user_id, meal_data) def analyze_food_with_ai(food_name: str, portion: str) -> Dict: """使用AI分析食物详细信息""" return smart_meal_recorder.food_db.analyze_food_with_ai(food_name, portion) def get_food_ai_suggestions(food_name: str) -> Dict: """获取食物的AI建议""" try: food_info = smart_meal_recorder.food_db.get_food_info(food_name) if food_info and food_info.get('ai_estimated'): return { 'health_tips': food_info.get('health_tips', ['保持均衡饮食']), 'cooking_suggestions': food_info.get('cooking_suggestions', ['简单烹饪']), 'confidence': food_info.get('confidence', 0.5) } else: # 如果数据库中没有AI分析结果，进行AI分析 analysis = analyze_food_with_ai(food_name, "适量") return { 'health_tips': analysis.get('health_tips', ['保持均衡饮食']), 'cooking_suggestions': analysis.get('cooking_suggestions', ['简单烹饪']), 'confidence': analysis.get('confidence', 0.5) } except Exception as e: print(f"获取AI建议失败: {e}") return { 'health_tips': ['保持均衡饮食'], 'cooking_suggestions': ['简单烹饪'], 'confidence': 0.3 } if __name__ == "__main__": # 测试智能食物数据库 print("测试智能食物数据库...") # 测试搜索 results = search_foods("鸡") print(f"搜索'鸡'的结果: {results}") # 测试分类 categories = get_food_categories() print(f"食物分类: {categories}") # 测试分量选项 portions = get_portion_options("鸡肉") print(f"鸡肉的分量选项: {portions}") # 测试热量估算 calories = estimate_calories("鸡肉", "1小块") print(f"1小块鸡肉的热量: {calories}卡路里") print("智能食物数据库测试完成！")